Abstract: A computer-implemented method, computer program product, and/or computing system for determining unexpected data includes: running for a given claim a machine learning term prediction model with first and second term types to predict third type terms in a specific domain that uses a machine learning term embedding model that has learned the correlation between term types in the specific domain; determining cohesiveness between the predicted third type terms and the actual third type terms from the given claim; determining a value score between the predicted third type terms and the actual third type; and running a machine learning propensity model using the value score determined for the given claim and context data for the given claim to determine if the given claim is unexpected.

Abstract: A system for 3D printing can include a printing device configured to create an object by depositing successive layers of uncured material and at least one mitigating device. At least one of the printing device and the at least one mitigating device can be configured to perform a method to mitigate a deformation of at least one of the successive layers of uncured material.

Abstract: Data relevancy-based data retention is provided. Data is assigned to a logical data retention relevancy compartment of a plurality of logical data retention relevancy compartments in a data lakehouse. It is determined whether a data retention relevancy value of the data is greater than a data retention threshold level of a data retention policy corresponding to the logical data retention relevancy compartment storing the data. The data is transferred from a physical data storage unit corresponding to the logical data retention relevancy compartment of the plurality of logical data retention relevancy compartments in the data lakehouse to an archive in response to determining that the data retention relevancy value of the data is greater than the data retention threshold level of the data retention policy corresponding to the logical data retention relevancy compartment storing the data.

Abstract: In an approach to optimize server connection timeout errors in a cloud environment, embodiments create a knowledge corpus associated with connection timeout patterns based on historical learning of transaction parameters and predicts a criticality of a transaction based on one or more identified contextual situations. Further, embodiments dynamically adjust a connection timeout range of the transaction based on the predicted criticality and one or more identified contextual situations of the transaction, and selectively identify a connection timeout range for the transaction based on an evaluation of the one or more contextual situations. Additionally, embodiments analyze generated timeout errors on a remote server from within a service mesh, and adjust timeout values of the transaction based on the analyzed generated timeouts errors. Responsive to the transaction receiving a timeout error, embodiments output a recommended timeline detailing when the transaction can be reinitiated.

Abstract: Embodiments of the present invention provide an approach for verifying a security and compliance standard of a multi-cloud environment based on a multi-cloud architecture diagram. Specially, the multi-cloud architecture diagram is parsed to verify the security and compliance standard checks. A list of resources and relationships are extracted from the multi-cloud architecture diagram and compared against an expected security standard compliance level. Any resources attributing non-compliance of the expected compliance level are identified by comparing the list of resources and relationships from the multi-cloud architectural diagram in a recursive and continuous manner. Only when security and compliance standard checks are satisfied/passed are the cloud resources deployed.

Abstract: Exploratory network analysis aided by an artificial intelligence recommender includes determining one or more current activities in response to detecting one or more processor-executable instructions input to a computer system by a user. A best next activity is predicted in response to matching the one or more current activities with an electronically stored pattern of activities. The predicting is performed using a machine learning model trained with knowledge components generated from patterns of past activities. A recommendation based on the best next activity is output, the recommendation recommending to the user one or more additional processor-executable instructions to input to the computer system.

Abstract: Computer-implemented methods, systems and program products establishing dynamically compliant and secure vehicle communication networks. Software bill of materials (SBOMs) are leveraged by route mapping services or other applications to ensure vehicle components and dependencies thereof comply with locational policies along a vehicle's route, as well as individual vehicle policies required to engage in vehicle-to-vehicle communications. Vehicle SBOMs are fetched and compared to policies for each location or zone a vehicle may pass through during a trip. Applicable policies can be set by government, or other institutions. Vehicles failing to comply with global policies of locations can be prevented from communicating or connecting to vehicle networks or may be re-routed to avoid locations where compliance is not achieved.

Abstract: Computer-implemented methods, systems and program products extending traditional cloud-centric intrusion detection to edge networks. NIDPS is decentralized between the edge and cloud. Edge gateways equipped with NIDPS agents capture packets of network traffic and pre-process the data. Pre-processing output is compressed and sent to cloud intrusion detection services equipped with latest available rules and signatures. As cloud IDS detects security threats using rules and signatures, NIDPS agents are alerted and switched from “lazy mode” to “preventative mode.” While in preventative mode, NIDPS agents inspect packets of network traffic in accordance with the rules and signatures associated with the detected security threat, dropping packets that trigger the rules and signatures, while still compressing and transmitting other packets to cloud IDS for analysis.

Abstract: In an approach to incremental clustering of continuous flow data streams to preserve data continuity, one or more computer processors receive a definition of a first major cluster period and a definition of a first minor cluster period. One or more computer processors receive a continuous stream of data. One or more computer processors cluster the continuous stream of data, based on the definition of the first major cluster period and on the definition of the first minor cluster period. One or more computer processors determine a similarity between a first data cluster and a second data cluster, wherein the second data cluster occurs after the first minor cluster period. One or more computer processors determine whether the similarity meets a pre-defined minimum threshold of similarity. One or more computer processors increase the first minor cluster period to a second minor cluster period.

Abstract: A computer-implemented method, according to one embodiment, includes dynamically assigning reputation scores to a plurality of tasks, and dynamically assigning reputation scores to a plurality of edge nodes. The method further includes dynamically placing the tasks into the edge nodes based on the reputation scores assigned to the tasks and the reputation scores assigned to the edge nodes. A computer program product, according to one embodiment, includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method. A system, according to another embodiment, includes a processor, and logic integrated with the processor, executable by the processor, or integrated with and executable by the processor. The logic is configured to perform the foregoing method.

Abstract: In an approach to incremental clustering of continuous flow data streams to preserve data continuity, one or more computer processors receive a definition of a first major cluster period and a definition of a first minor cluster period. One or more computer processors receive a continuous stream of data. One or more computer processors cluster the continuous stream of data, based on the definition of the first major cluster period and on the definition of the first minor cluster period. One or more computer processors determine a similarity between a first data cluster and a second data cluster, wherein the second data cluster occurs after the first minor cluster period. One or more computer processors determine whether the similarity meets a pre-defined minimum threshold of similarity. One or more computer processors increase the first minor cluster period to a second minor cluster period.

Abstract: Provided are a computer program product, system, and method for rendering an extended-reality representation of a virtual meeting. An extended reality representation is generated of a virtual meeting including avatars associated with participants in the virtual meeting to render in extended-reality displays of the participants. An extended-reality representation of a virtual controller corresponding to a real-world controller in a real-world location is generated to render in at least one extended-reality display of at least one participant in the virtual meeting. Participant input is received from one of the at least one participant to control the virtual controller. The participant input is translated to control the virtual controller to commands to control the real-world controller. The commands are transmitted to the real-world controller at the real-world location to control the real-world controller to perform actions in the real-world location to carry out the transmitted commands.

Abstract: A computer-implemented method for distributing packets for smart switching is provided. The computer-implemented method includes checking whether an edge device will complete a task relative to a data warehouse while having networking availability, deciding to proceed with the task using an extract, transform, load (ETL) strategy based on a determination that the edge device will complete the task while having the networking availability, checking whether the edge device will complete data extraction of the task while having the networking availability based on a determination that the edge device will not complete the task while having the networking availability and deciding to proceed with the data extraction using an extract, load, transform (ELT) strategy based on a determination that the edge device will complete the data extraction of the task while having the networking availability.

Abstract: A computer-implemented method, according to one embodiment, includes registering a plurality of software vendors to have access to an open channel and receiving, on the open channel, a plurality of software bill of materials (SBOMs) from the software vendors. Each SBOM is received from an associated one of the software vendors and details software versions that are currently offered by and/or scheduled to be released by the associated software vendor. The method further includes storing the received SBOMs in a predetermined database, and publishing the SBOMs on the open channel for the software vendors to access. A computer program product, according to another embodiment, includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method.

Abstract: A computer-implemented method, a computer system, and a computer program product are provided. A first computer receives first data from a first sensor associated with a first user. The first computer uses artificial intelligence to generate a first recommendation for a replacement object for the first user. The generating is based on the first data. The first recommendation indicates ability of the replacement object to replace a first object associated with the first user. The first computer transmits the first recommendation for presentation to the first user.

Abstract: A method, computer system, and a computer program product are provided for establishing security measures for a content. In one embodiment, the method comprises identifying at least a microservice chain in a network computer. Each microservice chain has more than one microservice linked to one another and each microservice includes a plurality of applications bundled together. Any use profiles associated with the microservice chain are identified and all data entry points into each microservice are determined. Each microservice is analyzed to predict when each microservice in the chain will provide a confidential output. Once any microservice chain is deemed to be providing a confidential output, any predicted exits in the microservice deemed to be generating an output content are upgraded so that all predicted exists provide a confidential output.

Abstract: A computer-implemented method, system and program product enabling communication and collaboration between autonomous vehicles and non-autonomous driving along a shared roadway. Autonomous vehicles having difficulty traveling along the roadway or making driving decisions due to the presence of non-autonomous vehicles request deployment of unmanned aerial vehicles (UAV). Based on the current driving conditions, the number of non-autonomous vehicles and other factors, a number of UAVs are deployed and attached to the non-autonomous vehicles. The UAVs scan the surrounding environment and nearby vehicles within the environment. UAVs transmit scanned images, sensor data and other information to the nearby autonomous vehicles which generate driving decisions based on the data collection of the autonomous vehicle in conjunction with data provided by UAVs. Driving decisions of autonomous vehicles are transmitted to the UAVs.

Abstract: A method of optimizing parameter data passing between microservices in a service mesh includes receiving, by a vertical reduction interceptor, a data reduction condition of a target microservice. The data reduction condition is provided by a vertical reduction database. The method further includes intercepting, by the vertical reduction interceptor, a sender microservice that sends the parameter data to the target microservice and reducing, upon identifying that the parameter data meets the data reduction condition of the target microservice, a dimension of the parameter data based on the data reduction condition. The parameter data is sent to the target microservice. The data reduction condition is based on a specified user profile.

Abstract: Systems, methods and/or computer program products predictively automating configurations of modular service zones servicing physical assets, maximizing reuse of service zone(s) and optimizing time for servicing a plurality of physical assets. Digital twin models of physical assets are classified, and arranged into workflows for the service zones, sequencing services performed on physical assets arriving at service centers and preparing service zones based on types of services requested, the estimated time of arrival and similarities between classifications of different digital twins of physical assets. Based on sequences of the workflow, arrival times of physical assets and overlap between parts, tools, machines, etc.

Abstract: A computer-implemented method, according to one embodiment, includes outputting a first virtual reality (VR) environment representation for display on a plurality of VR devices. First inputs received from participants using the VR devices are analyzed to determine whether to output a second VR environment representation. The method further includes determining, based on the analysis, a second VR environment representation and a first transitional sequence for the VR devices to output while transitioning from displaying the first VR environment representation to displaying the second VR environment representation. The second VR environment representation and the first transitional sequence are output for display on the VR devices.